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Functional connectivity between tumor region and resting-state networks as imaging biomarker for overall survival in recurrent gliomas diagnosed by O -(2-[18F]fluoroethyl)- l -tyrosine PET
No full textBackgroundAmino acid PET using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (FET) is one of the most reliable imaging methods for detecting glioma recurrence. Here, we hypothesized that functional MR connectivity between the metabolic active recurrent tumor region and resting-state networks of the brain could serve as a prognostic imaging biomarker for overall survival (OS).MethodsThe study included 82 patients (26–81 years; median Eastern Cooperative Oncology Group performance score, 0) with recurrent gliomas following therapy (WHO-CNS 2021 grade 4 glioblastoma, n = 57; grade 3 or 4 astrocytoma, n = 12; grade 2 or 3 oligodendroglioma, n = 13) diagnosed by FET PET simultaneously acquired with functional resting-state MR. Functional connectivity (FC) was assessed between tumor regions and 7 canonical resting-state networks.ResultsWHO tumor grade and IDH mutation status were strong predictors of OS after recurrence (P < .001). Overall FC between tumor regions and networks was highest in oligodendrogliomas and was inversely related to tumor grade (P = .031). FC between the tumor region and the dorsal attention network was associated with longer OS (HR, 0.88; 95%CI, 0.80–0.97; P = .007), and showed an independent association with OS (HR, 0.90; 95%CI, 0.81–0.99; P = .033) in a model including clinical factors, tumor volume and MGMT. In the glioblastoma subgroup, tumor volume and FC between the tumor and the visual network (HR, 0.90; 95%CI, 0.82–0.99, P = .031) were independent predictors of survival.ConclusionsRecurrent gliomas exhibit significant FC to resting-state networks of the brain. Besides tumor type and grade, high FC between the tumor and distinct networks could serve as independent prognostic factors for improved OS in these patients
Hydrogen Bonding Competition Mediated Phase Separation with Abnormal Moisture‐Induced Stiffness Boosting
No full textMoisture usually deteriorates polymers’ mechanical performance owing to its plasticizing effect, causing side effects in their practical load-bearing applications. Herein, a simple binary ionogel consisting of an amphiphilic polymer network and a hydrophobic ionic liquid (IL) is developed with remarkable stiffening effect after moisture absorption, demonstrating a complete contrast to water-induced softening effect of most polymer materials. Such a moisture-induced stiffening behavior is induced by phase separation after hydration of this binary ionogel. Specifically, it is revealed that hydrogen (H)-bonding structures play a dominant role in the humidity-responsive behavior of the ionogel, where water will preferentially interact with polymer chains through H-bonding and break the polymer-IL H-bonds, thus leading to phase separation structures with modulus boosting. This work may provide a facile and effective molecular engineering route to construct mechanically adaptive polymers with water-induced dramatic stiffening for diverse applications
Pseudocapacitive behavior in graphene oxide/NiO-polystyrene-block-polyisoprene-block-polystyrene triblock copolymer nanocomposites
No full textJuMonC: A RESTful tool for enabling monitoring and control of simulations at scale
No full textAs systems and simulations grow in size and complexity, it is challenging to maintain efficient use of resources and avoid failures. In this scenario, monitoring becomes even more important and mandatory. This paper describes and discusses the benefits of the advanced monitoring and control tool JuMonC, which runs under user control alongside HPC simulations and provides valuable metrics via REST-API. In addition, plugin extensibility allows JuMonC to go a step further and provide computational steering of the simulation itself. To demonstrate the benefits and usability of JuMonC for large-scale simulations, two use cases are described employing nekRS and ICON on JURECA-DC, a supercomputer located at the Jülich Supercomputing Centre (JSC). Furthermore, a large-scale use case with nekRS on JSC’s flagship system JUWELS Booster is described. Finally, the interplay between JuMonC and LLview (a standard monitoring tool for HPC systems) is presented using a simple and secure JuMonC-LLview plugin, which collects performance metrics and enables their analysis in LLview. Overall, the portability and usefulness of JuMonC, together with its low performance impact, make it an important application for both current and future generations of exascale HPC systems
Deciphering the Therapeutic Potential of Novel Pentyloxyamide-Based Class I, IIb HDAC Inhibitors against Therapy-Resistant Leukemia
No full textSulfur-resistant catalytic NO oxidation over surface-disproportionated CaMnO3 perovskites
No full textTransformationsverträge sind eine Sackgasse
No full textThis article analyses the impact of transformative agreements on the development of the open access landscape. It is shown that, regardless of their potential economic benefits, these transformative agreements do not effectively advance the transformation of the publishing industry because they do not sufficiently promote the flipping of subscription journals into open access journals. The flipping rates of two major publishers (Springer Nature and Wiley) and the results of the cOAlition S ‘Transformative Journals’ programme are examined using various approaches, with the result that the transformation of the majority of journals to open access via transformative agreements would take many decades. As a consequence, the authors call for greater promotion of Diamond Open Access as an alternative to transformation agreements, as well as for critical evaluation of transformation agreements before their renewal
Evolution of Reactive Organic Compounds and Their Potential Health Risk in Wildfire Smoke
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